BRAFV600E mutation impinges on gut microbial markers defining novel biomarkers for serrated colorectal cancer effective therapies

A Novel Neutrophil Extracellular Trap Signature Predicts Patient Chemotherapy Resistance and Prognosis in Lung Adenocarcinoma

Chemoresistance is a key obstacle in the long-term survival of patients with locally and advanced lung adenocarcinoma (LUAD). This study used bioinformatic analysis to reveal the chemoresistance of gene-neutrophil extracellular traps (NETs) associated with LUAD. RNA sequencing data and LUAD expression patterns were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, respectively. The GeneCards database was used to identify NETosis-related genes (NRGs). To identify hub genes with significant and consistent expression, differential analysis was performed using the TCGA-LUAD and GEO datasets. LUAD subtypes were determined based on these hub genes, followed by prognostic analysis. Immunological scoring and infiltration analysis were conducted using NETosis scores (N-scores) derived from the TCGA-LUAD dataset. A clinical prognostic model was established and analyzed, and its clinical applications explored. Twenty-two hub genes were identified, and consensus clustering was used to identify two subgroups based on their expression levels. The Kaplan-Meier (KM) curves demonstrated statistically significant differences in prognosis between the two LUAD subtypes. Based on the median score, patients were further divided into high and low N-score groups, and KM curves showed that the N-scores were more precise at predicting the prognosis of patients with LUAD for overall survival (OS). Immunological infiltration analysis revealed significant differences in the abundances of 10 immune cell infiltrates between the high and low N-score groups. Risk scores indicated significant differences in prognosis between the two extreme score groups. The risk scores for the prognostic model also indicated significant differences between the two groups. The results provide new insights into NETosis-related differentially expressed genes (NRDEGs) associated with chemotherapy resistance in patients with LUAD. The established prognostic model is promising and could help with clinical applications to evaluate patient survival and therapeutic efficiency.

Machine learning-derived diagnostic model of epithelial ovarian cancer based on gut microbiome signatures

BACKGROUND

Prior studies have elucidated that alterations in gut microbiota are associated with a spectrum of tumors and metabolic disorders. However, the diagnostic value of gut microbiota in epithelial ovarian cancer remains insufficiently investigated.

METHODS

A total of 34 patients with a diagnosis of epithelial ovarian cancer (EOC), 15 patients with benign ovarian tumors (TB), and 30 healthy volunteers (NOR) were enrolled in this study. Fecal samples were collected, followed by sequencing of the V3-V4 region of the 16S rRNA gene. The clinical data and pathological characteristics were comprehensively recorded for further analysis, PICRUSt2 was utilized to conduct an analysis of microbial functional predictions, WGCNA networks were constructed by integrating microbiome and clinical data. LEfSe analysis was employed to identify microbial diagnostic markers, LASSO and SVM analyses were used to screen microbial diagnostic markers in conjunction with the Cally index, to establish a Microbial-Cally diagnostic model. Bootstrap resampling was utilized for the internal validation of the model, whereas the Hosmer-Lemeshow test and decision curve analysis (DCA) were employed to evaluate the diagnostic performance of the model. Plasma samples were subjected to untargeted metabolomics profiling, followed by differential analysis to identify key metabolites that are significantly altered in epithelial ovarian cancer. At the same time, Spearman correlation analysis was used to study the association between key microbiota and differential metabolites. The supernatants from Escherichia coli and Bifidobacterium cultures were co-cultured with SKOV3 cells. Cell proliferation, migration, and invasion were evaluated using Cell Counting Kit-8 (CCK-8) assay, Transwell migration and invasion assays. Apoptosis was assessed by flow cytometry analysis of fluorescence signals from Annexin V and propidium iodide (PI) staining.

RESULTS

Compared to Nor and TB populations, individuals diagnosed with EOC demonstrated a significantly diminished gut microbiota diversity when contrasted with both normal controls and those presenting benign conditions. Specifically, the relative abundance of Bilophila, Bifidobacterium, and other probiotics was significantly reduced in patients diagnosed with epithelial ovarian cancer (EOC), while Escherichia and Shigella demonstrated a marked enrichment within this cohort. Differential microorganisms were identified through the application of machine learning techniques to delineate the characteristic microbial profiles associated with the EOC patients. A significant correlation was identified between the Cally index and microorganisms. In conclusion, we utilized microbial biomarkers alongside the Cally to establish a diagnostic model for epithelial ovarian cancer, receiver operating characteristic (ROC) curve Area Under Curve (AUC) of 0.976 (95%CI 0.943-1.00), The AUC obtained from the Bootstrap internal validation was 0.974. The Hosmer-Lemeshow test revealed a robust concordance between the observed probabilities and the predicted probabilities generated by the model. The decision curve analysis revealed that the model provided a significant net clinical benefit. A total of 233 differential metabolites were identified between the EOC group and the NT (NOR and TB) groups. Among these, eight specific metabolites (HMDB0243492, C09265, HMDB0242046, HMDB0240606, C04171, HMDB0060557, HMDB0252797, and C21412) were exclusively derived from the microbiome. Notably, metabolite HMDB0240606 exhibited a significant positive correlation with Escherichia coli and Shigella, while it showed a significant negative correlation with Ruminococcus. In vitro studies demonstrated that Bifidobacterium possessed anti-tumor activity, whereas Escherichia coli exhibited pro-tumor activity.

CONCLUSION

This study provides the inaugural comprehensive analysis of gut microbiota composition and its differential profiles among patients with epithelial ovarian cancer, those with benign ovarian tumors, and healthy controls in Hunan province, China.

Model systems to study tumor-microbiome interactions in early-onset colorectal cancer

Colorectal cancer (CRC) is a major health problem, with an alarming increase of early-onset CRC (EO-CRC) cases among individuals under 50 years of age. This trend shows the urgent need for understanding the underlying mechanisms leading to EO-CRC development and progression. There is significant evidence that the gut microbiome acts as a key player in CRC by triggering molecular changes in the colon epithelium, leading to tumorigenesis. However, a comprehensive collection and comparison of methods to study such tumor-microbiome interactions in the context of EO-CRC is sparse. This review provides an overview of the available in vivo, ex vivo as well as in vitro approaches to model EO-CRC and assess the effect of gut microbes on tumor development and growth. By comparing the advantages and limitations of each model system, it highlights that, while no single model is perfect, each is suitable for studying specific aspects of microbiome-induced tumorigenesis. Taken together, multifaceted approaches can simulate the human body's complexity, aiding in the development of effective treatment and prevention strategies for EO-CRC.

CCPred: Global and population-specific colorectal cancer prediction and metagenomic biomarker identification at different molecular levels using machine learning techniques

Colorectal cancer (CRC) ranks as the third most common cancer globally and the second leading cause of cancer-related deaths. Recent research highlights the pivotal role of the gut microbiota in CRC development and progression. Understanding the complex interplay between disease development and metagenomic data is essential for CRC diagnosis and treatment. Current computational models employ machine learning to identify metagenomic biomarkers associated with CRC, yet there is a need to improve their accuracy through a holistic biological knowledge perspective. This study aims to evaluate CRC-associated metagenomic data at species, enzymes, and pathway levels via conducting global and population-specific analyses. These analyses utilize relative abundance values from human gut microbiome sequencing data and robust classification models are built for disease prediction and biomarker identification. For global CRC prediction and biomarker identification, the features that are identified by SelectKBest (SKB), Information Gain (IG), and Extreme Gradient Boosting (XGBoost) methods are combined. Population-based analysis includes within-population, leave-one-dataset-out (LODO) and cross-population approaches. Four classification algorithms are employed for CRC classification. Random Forest achieved an AUC of 0.83 for species data, 0.78 for enzyme data and 0.76 for pathway data globally. On the global scale, potential taxonomic biomarkers include ruthenibacterium lactatiformanas; enzyme biomarkers include RNA 2' 3' cyclic 3' phosphodiesterase; and pathway biomarkers include pyruvate fermentation to acetone pathway. This study underscores the potential of machine learning models trained on metagenomic data for improved disease prediction and biomarker discovery. The proposed model and associated files are available at https://github.com/TemizMus/CCPRED.

Role of gut/liver metabolites and gut microbiota in liver fibrosis caused by cholestasis

AIM OF THE STUDY

Cholestasis induces severe liver injury and subsequent liver fibrosis. However, a comprehensive understanding of the relationships between liver fibrosis and cholestasis-induced changes in metabolites in the gut and fibrotic liver tissue and in the gut microbiota is insufficient.

METHODS

Common bile duct ligation (BDL) was employed to establish a cholestatic liver fibrosis model in mice for 26 days. Fibrotic liver tissue and the gut contents were collected. Untargeted metabolomics was conducted for the determination of metabolites in the gut contents and liver tissues. Metagenomics was adopted to explore the gut microbiota.

RESULTS

The metabolites in the gut contents and liver tissues between normal and cholestatic liver fibrosis mice were highly distinct. Beta-alanine metabolism and glutathione metabolism were downregulated in the gut of the BDL group. Galactose metabolism, biosynthesis of unsaturated fatty acids, and ABC transporters were upregulated in the gut and downregulated in the liver of the BDL group. Arginine biosynthesis, taurine and hypotaurine metabolism, arginine and proline metabolism, and primary bile acid biosynthesis were downregulated in the gut and upregulated in the liver of the BDL group. Metagenomic analysis revealed that the alpha diversity of the microbiota in the BDL group decreased. The altered structure of the gut microbiota in the BDL group led to the hypofunction of important metabolic pathways (such as folate biosynthesis, histidine metabolism, thiamine metabolism, biotin metabolism, and phenylalanine, tyrosine and tryptophan biosynthesis) and enzymes (such as NADH, DNA helicase, and DNA-directed DNA polymerase). Correlation analyses indicated that certain gut microbes were associated with gut and liver metabolites.

CONCLUSIONS

Untargeted metabolomics and metagenomics provided comprehensive information on gut and liver metabolism and gut microbiota in mice with cholestatic liver fibrosis. Therefore, significantly altered bacteria and metabolites may help provide some targets against cholestatic liver fibrosis in the future.

Role of blood metabolites in mediating the effect of gut microbiome on the mutated-RAS/BRAF metastatic colorectal cancer-specific survival

BACKGROUND

Recent studies have linked alterations in the gut microbiome and metabolic disruptions to the invasive behavior and metastasis of colorectal cancer (CRC), thus affecting patient prognosis. However, the specific relationship among gut microbiome, metabolite profiles, and mutated-RAS/BRAF metastatic colorectal cancer (M-mCRC) remains unclear. Furthermore, the potential mechanisms and prognostic implications of metabolic changes induced by gut microbiome alterations in patients with M-mCRC still need to be better understood.

METHODS

We conducted Mendelian randomization (MR) to evaluate the causal relationship of genetically predicted 196 gut microbiome features and 1400 plasma metabolites/metabolite ratios on M-mCRC-specific survival. Additionally, we identified significant gut microbiome-metabolites/metabolite ratio associations based on M-mCRC. Metabolite information was annotated, and functional annotation and pathway enrichment analyses were performed on shared proteins corresponding to significant metabolite ratios, aiming to reveal potential mechanisms by which gut microbiome influences M-mCRC prognosis via modulation of human metabolism.

RESULTS

We identified 11 gut microbiome features and 49 known metabolites/metabolite ratios correlated with M-mCRC-specific survival. Furthermore, we identified 17 gut microbiome-metabolite/metabolite ratio associations specific to M-mCRC, involving eight lipid metabolites and three bilirubin degradation products. The shared proteins corresponding to significant metabolite ratios were predominantly localized within the integral component of the membrane and exhibited enzymatic activities such as glucuronosyltransferase and UDP-glucuronosyltransferase, crucial in processes such as glucuronidation, bile secretion, and lipid metabolism. Moreover, these proteins were significantly enriched in pathways related to ascorbate and aldarate metabolism, pentose and glucuronate interconversions, steroid hormone biosynthesis, and bile secretion.

CONCLUSION

Our study offers novel insights into the potential mechanisms underlying the impact of the gut microbiome on the prognosis of M-mCRC. These findings serve as a meaningful reference for exploring potential therapeutic targets and strategies in the future.

A comprehensive overview of the molecular features and therapeutic targets in BRAFV600E-mutant colorectal cancer

As one of the most prevalent digestive system tumours, colorectal cancer (CRC) poses a significant threat to global human health. With the emergence of immunotherapy and target therapy, the prognosis for the majority of CRC patients has notably improved. However, the subset of patients with BRAF exon 15 p.V600E mutation (BRAFV600E) has not experienced remarkable benefits from these therapeutic advancements. Hence, researchers have undertaken foundational investigations into the molecular pathology of this specific subtype and clinical effectiveness of diverse therapeutic drug combinations. This review comprehensively summarised the distinctive molecular features and recent clinical research advancements in BRAF-mutant CRC. To explore potential therapeutic targets, this article conducted a systematic review of ongoing clinical trials involving patients with BRAFV600E-mutant CRC.

Molecular Frontiers in Melanoma: Pathogenesis, Diagnosis, and Therapeutic Advances

Melanoma, a highly aggressive skin cancer, is characterized by rapid progression and high mortality. Recent advances in molecular pathogenesis have shed light on genetic and epigenetic changes that drive melanoma development. This review provides an overview of these developments, focusing on molecular mechanisms in melanoma genesis. It highlights how mutations, particularly in the BRAF, NRAS, c-KIT, and GNAQ/GNA11 genes, affect critical signaling pathways. The evolution of diagnostic techniques, such as genomics, transcriptomics, liquid biopsies, and molecular biomarkers for early detection and prognosis, is also discussed. The therapeutic landscape has transformed with targeted therapies and immunotherapies, improving patient outcomes. This paper examines the efficacy, challenges, and prospects of these treatments, including recent clinical trials and emerging strategies. The potential of novel treatment strategies, including neoantigen vaccines, adoptive cell transfer, microbiome interactions, and nanoparticle-based combination therapy, is explored. These advances emphasize the challenges of therapy resistance and the importance of personalized medicine. This review underlines the necessity for evidence-based therapy selection in managing the increasing global incidence of melanoma.

Early-onset Colon Cancer Shows a Distinct Intestinal Microbiome and a Host-Microbe Interaction

The incidence rate of colorectal cancer in younger adults has been rising in developed countries. This trend may be attributed to environmental exposures as a result of lifestyle changes. Many of the lifestyle factors that promote colorectal cancer can also affect the gut microbiome, which may be associated with colorectal cancer risks. The role of the microbiome in the ongoing rise of early-onset colorectal cancer is unknown. Here, we aimed to investigate age-related differences in the gut microbiome of patients with colorectal cancer and healthy individuals by examining both the fecal and tumor microbiomes. We utilized the publicly accessible data on fecal shotgun metagenomics from CuratedMetagenomeData and TCGA via the GDC Data Portal. Comparison of 701 colorectal cancer and 693 controls revealed that microbial features were age dependent, with a significant difference in species enrichment between early-onset (<50 years) and late-onset (>65 years) patients with colorectal cancer. Analysis of the tumor-associated microbiome in a separate dataset of 85 patients with colorectal cancer verified age-specific differences in taxon abundance between early- and late-onset patients with colorectal cancer. Finally, using host gene expression data, we found a stronger microbe-host interaction in early- vs. late-onset colorectal cancers. Altogether, these findings indicate that microbial features were age-dependent with stronger microbial-host interactions at the tumor site in early-onset colorectal cancers, suggesting a direct role of microbes in tumorigenesis via interaction with cancer-related pathways in this age group.

PREVENTION RELEVANCE

Early-onset colorectal cancer is on the rise, presumably because of changes in environmental exposures. Lifestyle changes may contribute to colorectal cancer via alterations in gut microbes. Here, we show that microbial association with colorectal cancer is age-dependent, and microbe interactions with tumor pathways are stronger in young versus older colorectal cancers.

Recent Approaches on Molecular Markers, Treatment and Novel Drug Delivery System Used for the Management of Colorectal Cancer: A Comprehensive Review

Colorectal cancer affects 1 in 25 females and 1 in 24 males, making it the third most frequent cancer with over 6,08,030 deaths worldwide, despite advancements in detection and treatments, including surgery, chemotherapeutics, radiotherapy, and immune therapeutics. Novel potential agents have increased survival in acute and chronic disease conditions, with a higher risk of side effects and cost. However, metastatic disease has an insignificant long-term diagnosis, and significant challenges remain due to last-stage diagnosis and treatment failure. Early detection, survival, and treatment efficacy are all improved by biomarkers. The advancement of cancer biomarkers' molecular pathology and genomics during the last three decades has improved therapy. Clinically useful prognostic biomarkers assist clinical judgment, for example, by predicting the success of EGFR-inhibiting antibodies in the presence of KRAS gene mutations. Few biomarkers are currently used in clinical settings, so further research is still needed. Nanocarriers, with materials like Carbon nanotubes and gold nanoparticles, provide targeted CRC drug delivery and diagnostics. Light-responsive drugs with gold and silica nanoparticles effectively target and destroy CRC cells. We evaluate the potential use of the long non-coding RNA (non-coding RNA) oncogene plasmacytoma variant translocation 1 (PVT1) as a diagnostic, prognostic, and therapeutic biomarker, along with the latest nanotech breakthroughs in CRC diagnosis and treatment.

Machine learning: a powerful tool for identifying key microbial agents associated with specific cancer types

Machine learning (ML) includes a broad class of computer programs that improve with experience and shows unique strengths in performing tasks such as clustering, classification and regression. Over the past decade, microbial communities have been implicated in influencing the onset, progression, metastasis, and therapeutic response of multiple cancers. Host-microbe interaction may be a physiological pathway contributing to cancer development. With the accumulation of a large number of high-throughput data, ML has been successfully applied to the study of human cancer microbiomics in an attempt to reveal the complex mechanism behind cancer. In this review, we begin with a brief overview of the data sources included in cancer microbiomics studies. Then, the characteristics of the ML algorithm are briefly introduced. Secondly, the application progress of ML in cancer microbiomics is also reviewed. Finally, we highlight the challenges and future prospects facing ML in cancer microbiomics. On this basis, we conclude that the development of cancer microbiomics can not be achieved without ML, and that ML can be used to develop tumor-targeting microbial therapies, ultimately contributing to personalized and precision medicine.

Machine learning approaches in microbiome research: challenges and best practices

Microbiome data predictive analysis within a machine learning (ML) workflow presents numerous domain-specific challenges involving preprocessing, feature selection, predictive modeling, performance estimation, model interpretation, and the extraction of biological information from the results. To assist decision-making, we offer a set of recommendations on algorithm selection, pipeline creation and evaluation, stemming from the COST Action ML4Microbiome. We compared the suggested approaches on a multi-cohort shotgun metagenomics dataset of colorectal cancer patients, focusing on their performance in disease diagnosis and biomarker discovery. It is demonstrated that the use of compositional transformations and filtering methods as part of data preprocessing does not always improve the predictive performance of a model. In contrast, the multivariate feature selection, such as the Statistically Equivalent Signatures algorithm, was effective in reducing the classification error. When validated on a separate test dataset, this algorithm in combination with random forest modeling, provided the most accurate performance estimates. Lastly, we showed how linear modeling by logistic regression coupled with visualization techniques such as Individual Conditional Expectation (ICE) plots can yield interpretable results and offer biological insights. These findings are significant for clinicians and non-experts alike in translational applications.

Different states of stemness of glioblastoma stem cells sustain glioblastoma subtypes indicating novel clinical biomarkers and high-efficacy customized therapies

BACKGROUND

Glioblastoma (GBM) is the most malignant among gliomas with an inevitable lethal outcome. The elucidation of the physiology and regulation of this tumor is mandatory to unravel novel target and effective therapeutics. Emerging concepts show that the minor subset of glioblastoma stem cells (GSCs) accounts for tumorigenicity, representing the true target for innovative therapies in GBM.

METHODS

Here, we isolated and established functionally stable and steadily expanding GSCs lines from a large cohort of GBM patients. The molecular, functional and antigenic landscape of GBM tissues and their derivative GSCs was highlited in a side-by-side comprehensive genomic and transcriptomic characterization by ANOVA and Fisher's exact tests. GSCs' physio-pathological hallmarks were delineated by comparing over time in vitro and in vivo their expansion, self-renewal and tumorigenic ability with hierarchical linear models for repeated measurements and Kaplan-Meier method. Candidate biomarkers performance in discriminating GBM patients' classification emerged by classification tree and patients' survival analysis.

RESULTS

Here, distinct biomarker signatures together with aberrant functional programs were shown to stratify GBM patients as well as their sibling GSCs population into TCGA clusters. Of importance, GSCs cells were demonstrated to fully resemble over time the molecular features of their patient of origin. Furthermore, we pointed out the existence of distinct GSCs subsets within GBM classification, inherently endowed with different self-renewal and tumorigenic potential. Particularly, classical GSCs were identified by more undifferentiated biological hallmarks, enhanced expansion and clonal capacity as compared to the more mature, relatively slow-propagating mesenchymal and proneural cells, likely endowed with a higher potential for infiltration either ex vivo or in vivo. Importantly, the combination of DCX and EGFR markers, selectively enriched among GSCs pools, almost exactly predicted GBM patients' clusters together with their survival and drug response.

CONCLUSIONS

In this study we report that an inherent enrichment of distinct GSCs pools underpin the functional inter-cluster variances displayed by GBM patients. We uncover two selectively represented novel functional biomarkers capable of discriminating GBM patients' stratification, survival and drug response, setting the stage for the determination of patient-tailored diagnostic and prognostic strategies and, mostly, for the design of appropriate, patient-selective treatment protocols.

Genetic heterogeneity of colorectal cancer and the microbiome

In 2020, the International Agency for Research on Cancer and the World Health Organization's GLOBOCAN database ranked colorectal cancer (CRC) as the third most common cancer in the world. Most cases of CRC (> 95%) are sporadic and develop from colorectal polyps that can progress to intramucosal carcinoma and CRC. Increasing evidence is accumulating that the gut microbiota can play a key role in the initiation and progression of CRC, as well as in the treatment of CRC, acting as an important metabolic and immunological regulator. Factors that may determine the microbiota role in CRC carcinogenesis include inflammation, changes in intestinal stem cell function, impact of bacterial metabolites on gut mucosa, accumulation of genetic mutations and other factors. In this review, I discuss the major mechanisms of the development of sporadic CRC, provide detailed characteristics of the bacteria that are most often associated with CRC, and analyze the role of the microbiome and microbial metabolites in inflammation initiation, activation of proliferative activity in intestinal epithelial and stem cells, and the development of genetic and epigenetic changes in CRC. I consider long-term studies in this direction to be very important, as they open up new opportunities for the treatment and prevention of CRC.

Implication of gut microbes and its metabolites in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is the third most common cancer with a significant impact on loss of life. In 2020, nearly 1.9 million new cases and over 9,35,000 deaths were reported. Numerous microbes that are abundant in the human gut benefit host physiology in many ways. Although the underlying mechanism is still unknown, their association appears to be crucial in the beginning and progression of CRC. Diet has a significant impact on the microbial composition and may increase the chance of getting CRC. Increasing evidence points to the gut microbiota as the primary initiator of colonic inflammation, which is connected to the development of colonic tumors. However, it is unclear how the microbiota contributes to the development of CRCs. Patients with CRC have been found to have dysbiosis of the gut microbiota, which can be identified by a decline in commensal bacterial species, such as those that produce butyrate, and a concurrent increase in harmful bacterial populations, such as opportunistic pathogens that produce pro-inflammatory cytokines. We believe that using probiotics or altering the gut microbiota will likely be effective tools in the fight against CRC treatment.

PURPOSE

In this review, we revisited the association between gut microbiota and colorectal cancer whether cause or effect. The various factors which influence gut microbiome in patients with CRC and possible mechanism in relation with development of CRC.

CONCLUSION

The clinical significance of the intestinal microbiota may aid in the prevention and management of CRC.

WJOG13219G: The Efficacy and Safety of FOLFOXIRI or Doublet plus Anti-VEGF Therapy in Previously Untreated BRAFV600E Mutant Metastatic Colorectal Cancer: A Multi-Institutional Registry-Based Study (BRACELET Study)

BACKGROUND

The real-world survival benefit of FOLFOXIRI (fluorouracil, leucovorin, oxaliplatin, and irinotecan) plus anti-VEGF therapy (Triplet) over doublet chemotherapy (Doublet) remains controversial in patients with BRAF^V600E mutant metastatic colorectal cancer (mCRC).

PATIENTS AND METHODS

WJOG13219G was a multicenter, retrospective, registry-based study of patients with BRAF^V600E mutant mCRC who received first-line triplet or doublet chemotherapy from January 2014 to December 2019 in Japan. Inverse probability of treatment weighting (IPTW) was used to adjust for patient background.

RESULTS

The analysis included 79 and 91 patients in the Triplet and Doublet groups, respectively. The Triplet group was significantly younger and had better performance status. No statistical difference was noted in progression-free survival (PFS; HR, 0.82; 95% CI, 0.60-1.13; P = .22) and overall survival (OS; HR, 0.88; 95% CI, 0.62-1.25; P = .48) between both groups. IPTW analysis also showed no difference between the 2 groups in PFS (HR, 0.86; 95% CI, 0.69-1.08; P = .20) and OS (HR, 0.93; 95% CI, 0.73-1.20; P = .59). The Triplet and Doublet groups had an objective response rate of 53% and 41%, respectively (P = .10). At least one grade 3 or 4 adverse event was seen in 51 (65%) and 43 (47%) patients in the Triplet and Doublet groups, respectively, with the incidence of neutropenia being significantly higher in the former.

CONCLUSION

Triplet therapy had no survival benefit versus doublet therapy in the overall and IPTW cohorts or specific subgroups for real-world patients with BRAF^V600E mutant mCRC.

Gut Microbiota and Therapy in Metastatic Melanoma: Focus on MAPK Pathway Inhibition

Gut microbiome (GM) and its either pro-tumorigenic or anti-tumorigenic role is intriguing and constitutes an evolving landscape in translational oncology. It has been suggested that these microorganisms may be involved in carcinogenesis, cancer treatment response and resistance, as well as predisposition to adverse effects. In melanoma patients, one of the most immunogenic cancers, immune checkpoint inhibitors (ICI) and MAPK-targeted therapy—BRAF/MEK inhibitors—have revolutionized prognosis, and the study of the microbiome as a modulating factor is thus appealing. Although BRAF/MEK inhibitors constitute one of the main backbones of treatment in melanoma, little is known about their impact on GM and how this might correlate with immune re-induction. On the contrary, ICI and their relationship to GM has become an interesting field of research due to the already-known impact of immunotherapy in modulating the immune system. Immune reprogramming in the tumor microenvironment has been established as one of the main targets of microbiome, since it can induce immunosuppressive phenotypes, promote inflammatory responses or conduct anti-tumor responses. As a result, ongoing clinical trials are evaluating the role of fecal microbiota transplant (FMT), as well as the impact of using dietary supplements, antibiotics and probiotics in the prediction of response to therapy. In this review, we provide an overview of GM’s link to cancer, its relationship with the immune system and how this may impact response to treatments in melanoma patients. We also discuss insights about novel therapeutic approaches including FMT, changes in diet and use of probiotics, prebiotics and symbiotics. Finally, we hypothesize on the possible pathways through which GM may impact anti-tumor efficacy in melanoma patients treated with targeted therapy, an appealing subject of which little is known.

The gut microbiome and melanoma: A review

Disturbances in the microbial ecosystem have been implemented in chronic inflammation, immune evasion and carcinogenesis, with certain microbes associated with the development of specific cancers. In recent times, the gut microbiome has been recognised as a potential novel player in the pathogenesis and treatment of malignant melanoma. It has been shown that the composition of gut microbiota in early-stage melanoma changes from in situ to invasive and then to metastatic disease. The gut bacterial and fungal profile has also been found to be significantly different in melanoma patients compared to controls. Multiple studies of immune checkpoint inhibitor (ICI) therapies have shown that the commensal microbiota may have an impact on anti-tumor immunity and therefore ICI response in cancer patients. When it comes to chemotherapy and radiotherapy treatments, studies demonstrate that gut microbiota are invaluable in the repair of radiation and chemotherapy-induced damage and therapeutic manipulation of gut microbiota can be an effective strategy to deal with side effects. Studies demonstrate the oncogenic and tumor-suppressive properties of the gut microbiome, which may play a role in the pathogenesis of melanoma. Despite this, investigations into specific interactions are still in its infancy, but starting to gain momentum as more significant and clinically relevant effects are emerging.

Butyrate, a postbiotic of intestinal bacteria, affects pancreatic cancer and gemcitabine response in in vitro and in vivo models

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer. The characteristic excessive stromatogenesis accompanying the growth of this tumor is believed to contribute to chemoresistance which, together with drug toxicity, results in poor clinical outcome. An increasing number of studies are showing that gut microbiota and their metabolites are implicated in cancer pathogenesis, progression and response to therapies. In this study we tested butyrate, a product of dietary fibers' bacterial fermentation, whose anticancer and anti-inflammatory functions are known. We provided in vitro evidence that, beside slowing proliferation, butyrate enhanced gemcitabine effectiveness against two human pancreatic cancer cell lines, mainly inducing apoptosis. In addition, we observed that, when administered to a PDAC mouse model, alone or combined with gemcitabine treatment, butyrate markedly reduced the cancer-associated stromatogenesis, preserved intestinal mucosa integrity and affected fecal microbiota composition by increasing short chain fatty acids producing bacteria and decreasing some pro-inflammatory microorganisms. Furthermore, a biochemical serum analysis showed butyrate to ameliorate some markers of kidney and liver damage, whereas a metabolomics approach revealed a deep modification of lipid metabolism, which may affect tumor progression or response to therapy. Such results support that butyrate supplementation, in addition to conventional therapies, can interfere with pancreatic cancer biology and response to treatment and can alleviate some damages associated to cancer itself or to chemotherapy.

Alterations in the Gut Microbiota and Their Metabolites in Colorectal Cancer: Recent Progress and Future Prospects

Colorectal cancer (CRC) is a leading cause of cancer morbidity and mortality worldwide. The etiology and pathogenesis of CRC remain unclear. A growing body of evidence suggests dysbiosis of gut bacteria can contribute to the occurrence and development of CRC by generating harmful metabolites and changing host physiological processes. Metabolomics, a systems biology method, will systematically study the changes in metabolites in the physiological processes of the body, eventually playing a significant role in the detection of metabolic biomarkers and improving disease diagnosis and treatment. Metabolomics, in particular, has been highly beneficial in tracking microbially derived metabolites, which has substantially advanced our comprehension of host-microbiota metabolic interactions in CRC. This paper has briefly compiled recent research progress of the alterations of intestinal flora and its metabolites associated with CRC and the application of association analysis of metabolomics and gut microbiome in the diagnosis, prevention, and treatment of CRC; furthermore, we discuss the prospects for the problems and development direction of this association analysis in the study of CRC. Gut microbiota and their metabolites influence the progression and causation of CRC, and the association analysis of metabolomics and gut microbiome will provide novel strategies for the prevention, diagnosis, and therapy of CRC.

Lactiplantibacillus plantarum HNU082 inhibited the growth of Fusobacterium nucleatum and alleviated the inflammatory response introduced by F. nucleatum invasion

As a potential biomarker, there is increasing evidence showing that Fusobacterium nucleatum is positively correlated with the occurrence and development of colorectal cancer. Although antibiotics were expected to eliminate F. nucleatum, the side effects associated with gut microbiotal disorders have to be considered. Here, by performing shotgun metagenomic and transcriptome sequencing, we systematically evaluated the antagonistic effects of probiotic Lactiplantibacillus plantarum HNU082 (Lp082) on F. nucleatum in vivo and in vitro. The results showed that the F. nucleatum invasion significantly altered the host intestinal microbiome including the microbial composition, specific species, metabolic pathways and metabolites, as well as impacted the transcriptome of the intestinal epithelial cells. Moreover, the F. nucleatum invasion triggered inflammatory cytokines and inflammatory responses in the intestine but did not develop into colorectal cancer. Excitingly, the Lp082 intervention inhibited the growth of F. nucleatum both in vivo and in vitro and alleviated the inflammatory response introduced by F. nucleatum invasion. Further network-based mechanism exploration demonstrated that Lp082, which negatively correlated to F. nucleatum, maintained the intestinal microbiome homeostasis and prompted the production of beneficial metabolites in the intestine which decreased the expression of inflammatory cytokines in a mouse model. The present research suggested a feasible probiotic intervention strategy for F. nucleatum antagonism in vivo, which may prevent colorectal cancer at the early stage.