Tumor microbiota of renal cell carcinoma affects clinical prognosis by influencing the tumor immune microenvironment.

Despite reported influences of the intratumoral microbiome on cancer progression, its role in this subtype remains unclear. This study aimed to characterize the microbial landscape and signatures of kidney renal clear cell carcinoma using RNA-Seq data from The Cancer Genome Atlas. Following microbial decontamination, differential microbial analysis was conducted between tumorous and adjacent non-tumorous samples. Compared to non-tumorous samples, tumorous microbiota exhibited reduced α and ß diversity and distinct phylum-level communities. Differential microbial analysis between patients exhibiting long and short overall survival revealed ten significant differential microbial genera, with six genera correlating with a positive prognosis (Plasmodium, Babesia, Toxoplasma, Cytobacillus, Alicyclobacillus, Verrucomicrobium) and four with a negative prognosis (Colletotrichum, Leuconostoc, Gluconobacter, and Parabacteroides). Employing Cox regression analysis and support vector machines, a prognosis-related microbiome risk signature was developed, achieving an AUC of 0.809. Based on this risk signature, two microbiome-based subtypes were found to be significantly associated with distinct clinical prognoses and immune microenvironments. These findings were corroborated by significant correlations between prognostic-relevant microorganisms and 30 immune-related differentially expressed genes. Specifically, microbial genera associated with a negative prognosis were linked to a pro-tumor acute inflammatory immune response, whereas genera related to a positive prognosis were associated with an anti-tumor adaptive immune response. In conclusion, microbiome-based subtyping revealed correlations between tumor microbiome, clinical prognosis, and tumor microenvironment, indicating intratumoral microbiota as a promising prognostic biomarker for kidney renal clear cell carcinoma.

Intratumoral microbiota of pancreatic ductal adenocarcinoma impact patient prognosis by influencing tumor microenvironment.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is characterized by a highly metastatic potential and a heterogeneous tumor microenvironment. It exhibits limited sensitivity to conventional therapies, necessitating a deeper understanding of its pathogenesis. The role of the intratumoral microbiome in regulating cancer development in PDAC has been the subject of debate. Previous investigations into intra-tumor microbiomes have yielded uncertain results due to sample size limitations and insufficient decontamination procedures. Further research is imperative to elucidate the intricate relationship between intra-tumor microbiomes, the immune landscape of PDAC, and overall prognosis. RESULTS: Our findings revealed that the intratumor microbiota in PDAC tissue exhibited lower diversity and distinct communities compared to non-tumor tissues. The top microorganisms distinguishing between patients with long or short survival were used to construct the risk signature. We found that Stenotrophomonas is implicated in short survival of PDAC patients, while Neorickettia and Mediterraneibacter are correlated with long survival. This microbiome-based PDAC subtyping, grounded in prognosis-related signatures, exhibited significant correlations with distinct clinical prognoses and immune microenvironments. Microorganisms associated with negative prognoses were linked to pro-tumor immune activation, while those associated with positive prognoses were linked to anti-tumor immune response activation and a more favorable prognosis. CONCLUSIONS: Our PDAC subtyping approach, based on a microbiome-derived prognostic risk signature, unveiled compelling associations between the PDAC microbiota and disparities in both clinical prognosis and the tumor microenvironment. These findings suggest that microbiota may serve as a promising biomarker for predicting the prognosis of PDAC.

T1 and T2 mapping for identifying malignant lymph nodes in head and neck squamous cell carcinoma.

BACKGROUND: This study seeks to assess the utility of T1 and T2 mapping in distinguishing metastatic lymph nodes from reactive lymphadenopathy in patients with head and neck squamous cell carcinoma (HNSCC), using diffusion-weighted imaging (DWI) as a comparison. METHODS: Between July 2017 and November 2019, 46 HNSCC patients underwent neck MRI inclusive of T1 and T2 mapping and DWI. Quantitative measurements derived from preoperative T1 and T2 mapping and DWI of metastatic and non-metastatic lymph nodes were compared using independent samples t-test or Mann-Whitney U test. Receiver operating characteristic curves and the DeLong test were employed to determine the most effective diagnostic methodology. RESULTS: We examined a total of 122 lymph nodes, 45 (36.9%) of which were metastatic proven by pathology. Mean T2 values for metastatic lymph nodes were significantly lower than those for benign lymph nodes (p < 0.001). Conversely, metastatic lymph nodes exhibited significantly higher apparent diffusion coefficient (ADC) and standard deviation of T1 values (T1SD) (p < 0.001). T2 generated a significantly higher area under the curve (AUC) of 0.890 (0.826-0.954) compared to T1SD (0.711 [0.613-0.809]) and ADC (0.660 [0.562-0.758]) (p = 0.007 and p < 0.001). Combining T2, T1SD, ADC, and lymph node size achieved an AUC of 0.929 (0.875-0.983), which did not significantly enhance diagnostic performance over using T2 alone (p = 0.089). CONCLUSIONS: The application of T1 and T2 mapping is feasible in differentiating metastatic from non-metastatic lymph nodes in HNSCC and can improve diagnostic efficacy compared to DWI.

Interaction between intratumoral microbiota and tumor mediates the response of neoadjuvant therapy for rectal cancer.

Background: Previous observations have demonstrated that the response to neoadjuvant chemoradiotherapy (nCRT) is highly variable in patients with locally advanced rectal cancer (LARC). Recent studies focusing on the intratumoral microbiota of colorectal cancer have revealed its role in oncogenesis and tumor progression. However, limited research has focused on the influence of intratumoral microbiota on the nCRT of LARC. Methods: We explored the microbial profiles in the tumor microenvironment of LARC using RNA-seq data from a published European cohort. Microbial signatures were characterized in pathological complete response (pCR) and non-pCR groups. Multi-omics analysis was performed between intratumor microbiomes and transcriptomes. Results: Microbial α and ß diversity were significantly different in pCR and non-pCR groups. Twelve differential microbes were discovered between the pCR and non-pCR groups, six of which were related to subclusters of cancer-associated fibroblasts (CAFs) associated with extracellular matrix formation. A microbial risk score based on the relative abundance of seven differential microbes had predictive value for the nCRT response (AUC = 0.820, p < 0.001). Conclusion: Our study presents intratumoral microbes as potential independent predictive markers for the response of nCRT to LARC and demonstrates the underlying mechanism by which the interaction between intratumoral microbes and CAFs mediates the response to nCRT.

Free-Breathing StarVIBE Sequence for the Detection of Extranodal Extension in Head and Neck Cancer: An Image Quality and Diagnostic Performance Study.

(1) Background: This study aims to evaluate the image quality of abnormal cervical lymph nodes in head and neck cancer and the diagnostic performance of detecting extranodal extension (ENE) using free-breathing StarVIBE. (2) Methods: In this retrospective analysis, 80 consecutive head and neck cancer patients underwent StarVIBE before neck dissection at an academic center. Image quality was compared with conventional VIBE available for 28 of these patients. A total of 73 suspicious metastatic lymph nodes from 40 patients were found based on morphology and enhancement pattern on StarVIBE. Sensitivity (SN), specificity (SP), and odds ratios were calculated for each MR feature from StarVIBE to predict pathologic ENE. (3) Results: StarVIBE showed significantly superior image quality, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) for enlarged lymph nodes compared to VIBE. The MR findings of "invading adjacent planes" (SN, 0.54; SP, 1.00) and "matted nodes" (SN, 0.72; SP, 0.89) emerged as notable observations. The highest diagnostic performance was attained by combining these two features (SN, 0.93; SP, 0.89). (4) Conclusions: This study confirms that StarVIBE offers superior image quality for abnormal lymph nodes compared to VIBE, and it can accurately diagnose ENE by utilizing a composite MR criterion in head and neck cancer.

Intratumoural microbiome can predict the prognosis of hepatocellular carcinoma after surgery.

BACKGROUND: The dismal prognosis of hepatocellular carcinoma (HCC) is closely associated with characteristics of the tumour microenvironment (TME). Recent studies have confirmed the presence and potential influence of the microbiome in TME on cancer progression. Elucidating the relationship between microbes in the TME and cancer could provide valuable insights into novel diagnostic markers and therapeutic strategies for HCC and thus warrants a closer investigation of the role of intratumoural microbiome in the HCC TME. METHODS: We determined the presence of intratumoural microbiome using fluorescence in situ hybridisation, and explored the microbial community profiles in the HCC TME in paired tumour and adjacent normal tissues using 16S rDNA sequencing. Microbial signatures were characterised in the paired group, and their correlation with clinical characteristics was further investigated. We clustered the microbial signatures of tumour tissues by hepatotypes, and further analysis was performed to elucidate the independent prognostic value of the hepatotypes. RESULTS: This study revealed that microbial profiles and community networks differed notably between tumours and adjacent normal tissues. Proteobacteria and Actinobacteria were the most abundant phyla in the HCC TME. The TME microbial profiles also revealed heterogeneities between individuals and between multiple tumour lesions. Clustering of the microbial profiles into two hepatotypes revealed different microbial network patterns. Additionally, the hepatotypes were revealed to be independent prognostic factors in patients with resected HCC. CONCLUSIONS: Our study illuminates the microbial profiles in the TME of HCC and presents the hepatotype as a potential independent biomarker for the prognostic prediction of HCC after surgery.